Phenotypic Resistance of Bacteria Isolated from Urinary Tract Infections at the Protestant Hospital of Ngaoundere (Cameroon)

Abstract

Aims and objectives: The frequent and unprescribed use of antibiotics has led to the development of resistance by microorganisms responsible for urinary tract infection (UTI). In order to facilitate the follow-up of this microbial resistance, the aim of this study was to determine the bacteria resistant phenotypes. Method: To achieve the following objectives, this study was conducted from June to August 2023. The isolation and identification were performed by standard methods why susceptibility testing was done by Kirby-Bauer disk diffusion technique according to CLSI guidelines. Double-disk synergy test was applied to determine the presence of extended-spectrum β-lactamase (ESBL) produced by bacteria. The Imipenem EDTA Combined Disc Test (CDT) for Metallo beta lactamase (MBL) screening, the D-zone test to detect macrolides, lincosamides and streptogramins type B (MLSB) and Meticillin resistant Staphylococcus aureus (MRS A) which was assessed using a Cefoxitin (30 µg) disc. Results: A total of 40 bacteria were identified with a prevalence of 37.03%. Overall, E. coli was the predominant isolate 14 (35%), followed by Staphylococcus aureus 10 (25%) and Klesbsiella pneumonia 4 (10%). Pseudomonas aeruginosa, Salmonella arinosa and Enterobacter were the most sensible (100%) bacteria against ciprofloxin, ceftriaxone and cefixime. Almost all bacteria were resistant to Amoxicillin/clavulanic acid (>50%). The isolates were in the majority resistant to imipenem. ESBL-producing Enterobacteriaceae represented 25.92%, with a higher rate among E. coli. No MBL production was found among the isolates while 38.46% represented cMLSB, 15.38% represented iMLSB, 23.07% represented MSB and 23.07% represented MRSA. Conclusion: Clinical strains of UTI from Protestant Hospital of Ngaoundere exhibiting ESBL, cMLSB, iMLSB, MSB and MRSA. The regular updating of antibiotic resistance statistics of isolated strains allows for a better adaptation of probabilistic antibiotic therapy.